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@@ -11,6 +11,7 @@ license: apache-2.0
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  ## Dataset Description
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  This dataset includes 8 episodes of pong-v4 environment. The expert policy is EfficientZero, which is able to generate MCTS hidden states.
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  ## Dataset Structure
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  ### Data Instances
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  A data point comprises tuples of sequences of (observations, actions, hidden_states):
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  - `hidden_state`: An Array3D containing corresponding hidden states generated by EfficientZero, from 8 trajectories of an evaluated agent. The data type is float32.
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  ### Data Splits
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- There is only a training set for this dataset, as evaluation is undertaken by interacting with a simulator.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Dataset Description
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  This dataset includes 8 episodes of pong-v4 environment. The expert policy is EfficientZero, which is able to generate MCTS hidden states.
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+ ## Supported Tasks and Leaderboards
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  ## Dataset Structure
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  ### Data Instances
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  A data point comprises tuples of sequences of (observations, actions, hidden_states):
 
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  - `hidden_state`: An Array3D containing corresponding hidden states generated by EfficientZero, from 8 trajectories of an evaluated agent. The data type is float32.
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  ### Data Splits
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+ There is only a training set for this dataset, as evaluation is undertaken by interacting with a simulator.
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+
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+ ## Dataset Creation
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+ ### Curation Rationale
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+ - TBD
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+
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+ ### Source Data
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+ #### Initial Data Collection and Normalization
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+ - TBD
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+
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+ #### Who are the source language producers?
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+ - TBD
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+
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+ #### Annotations
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+ - TBD
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+
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+ ## Considerations for Using the Data
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+ ### Known Limitations
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+ - TBD
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+
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+ ## Additional Information
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+
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+ ### Licensing Information
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+ - TBD
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+
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+ ### Citation Information
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+
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+ ```
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+ TBD
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+
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+ ```
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+
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+ ### Contributions
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+ Thanks to [@test](test_url), for adding this dataset.
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+ [How to contribute to Datasets](https://files.pushshift.io/reddit/)